It is often desirable or necessary to determine if a particular applicant seeking to use an electronic service remotely is in fact a human being, and not an automated system. For example, web sites on the Internet that offer access for free to humans but want to restrict automated programs (sometimes referred to as “bots”) from abusing their system need a way to distinguish between the two. This is often the case in situations where normal human usage would put an acceptable load on a server that automated processes could easily exceed. Additionally, in many cases bots are designed to use computer system services for purposes that they are not intended for, such as mass registering for free email accounts that are then used to send unsolicited advertising.
Currently, a commonly used automated method for making the determination of whether an applicant for access to a secured service or computer system is a human or is a bot is what is known as a reverse Turing test (RTT). This can involve presenting the applicant with an image (or a data set convertible into an image), which can, for example, contain either a string of characters or a picture of a readily recognizable object, and having the user identify what is presented in the image. Typically the images presented to the users are distorted in an attempt to make it more difficult for Optical Character Recognition (OCR) software, and other visual recognition programs, to determine what the image is (thereby allowing automated systems to fool the process of identifying whether a user is in fact human). One of the problems being encountered is that as the methods for identifying text and images by computer programs advance, the images must be obfuscated or distorted more and more, increasing the difficulty for a human user to identify the images as well. Therefore a method of increasing the difficulty for a machine or bot to pass an RTT, without increasing the difficulty for a human user, is highly desirable.